MSI Authentication failed in Azure Machine Learning Online endpoint deployment

Question

I'm trying to deploy a managed online endpoint on Azure Machine Learning workspace but I'm having a MSI authentication problem when trying to authenticate with my workspace from my score.py script using managed-identities. I have checked if my workspace identity is a system-managed assigned identity and yes it is, also having its tenant ID. This is the main cause of the error from the deployment logs:

Answer 1

The error you are encountering indicates that the deployment is having trouble connecting to the Managed Service Identity (MSI) for authentication in Azure Machine Learning (AML). The error message Failed to connect to MSI and the response code [405] typically suggests that there might be a configuration issue with the MSI or that it’s being used in a context where it's not accessible.

Here are some steps you can follow to resolve the issue:

1. Ensure Managed Identity is Enabled

• Double-check that the Azure Machine Learning workspace has a system-assigned managed identity enabled. You can do this in the Azure portal:
  • Navigate to your Azure Machine Learning workspace.
  • Under Settings, select Identity.
  • Ensure that the System-assigned managed identity is enabled.

2. Correct MSI Permissions

• Ensure that the managed identity assigned to your workspace has the appropriate permissions to access the required resources. You need to assign the necessary RBAC roles to the MSI (e.g., Contributor, Reader, AI Training Operator, etc., depending on the resources the script interacts with).
• To assign roles:
  1. Go to Access control (IAM) of the target resources (e.g., Azure Storage, Key Vault, or other resources being accessed by the score.py script).
  2. Assign the managed identity to the appropriate role.

3. Verify MSI Access to Azure Resources

• Ensure that your score.py script is correctly configured to authenticate using MSI:
  • In your Python script, use the Azure Identity SDK to authenticate via the managed identity:

  
       from azure.identity import ManagedIdentityCredential
  
       from azure.ai.ml import MLClient
  
       # Use Managed Identity Credential
  
       credential = ManagedIdentityCredential()
  
       ml_client = MLClient(credential, subscription_id, resource_group_name, workspace_name)
  
  

4. Check Network Settings

• Ensure that there are no network restrictions or firewalls that might block MSI from being accessible. You can check this by verifying if the endpoint where the score.py is running can access Azure services.
  • If your workspace or deployment is part of a Virtual Network (VNet), ensure that the Managed Identity endpoint is accessible from within the network.

5. Confirm Endpoint Deployment

• If you are deploying a managed online endpoint, ensure that the deployment is correctly configured to use the managed identity. Check the following:
  • In the deployment YAML, make sure the identity is set to SystemAssigned for the deployment.
  Example:

  
       identity:
  
         type: SystemAssigned
  
  

6. Retry After Some Time

• In some cases, the managed identity may not be fully propagated or available immediately after being enabled. Wait for a few minutes and try the deployment again.

7. Check Azure CLI Version

• Ensure that you are using the latest version of the Azure CLI. Sometimes, older versions of the CLI may have bugs that prevent MSI from functioning correctly.

To update the Azure CLI:

   az upgrade

If the issue persists after following these steps, try redeploying the endpoint or sharing additional logs for further debugging.